A biomarker discovery process using mass spectrometry data has several challenges. One of them is the amount of LC/MS data generated by the instrument for a biological experiment. For example, an average mass spectrometry file can be up to 10 gigabytes and an experiment with 100 samples will be 1 terabyte of data. These data need to be processed using CPU- and memory-extensive image-processing and statistical methods to detect peaks of interest as the potential biomarkers. Future increases in the precision and efficiency of mass spectrometers will increase the above-noted challenges—by potentially providing the capacity to generate even greater volumes of mass spectrometry data over decreasing spans of time.